News

Dilakshan Srikanthan Secures Third Place at National 3MT Competition

Dilakshan Srikanthan Secures Third Place at National 3MT Competition

Congratulations to Dilakshan Srikanthan, MD/PhD student in Translational Medicine at Queen’s and Med-i CREATE trainee, for achieving Third Place at the 2025 National 3MT Showcase competition held in Ottawa! See more information on Queen's Gazette
Welcome to Our Newest Cohort in the CREATE Training Program in Medical Informatics

Welcome to Our Newest Cohort in the CREATE Training Program in Medical Informatics

On October 9, we welcomed the latest cohort of trainees to the Med-i CREATE program. Both new and current students participated in a mandatory session hosted by the Experiential Learning Hub at Queen’s University, which was followed by an orientation and welcome address from Principal Investigator Dr. Parvin Mousavi. Students from Western University joined both sessions remotely.
Med-i CREATE Master’s Students Successfully Complete Their Degrees

Med-i CREATE Master’s Students Successfully Complete Their Degrees

Congratulations to Med-i CREATE Master’s students Tyler Elliott, Maha Kesibi, E Ching Kho, Bining Long, and Sarah Nassar on successfully completing their degrees.
Emma Willis and Vivian Nguyen Awarded Canada Graduate Scholarships-Master’s for 2025-2026

Emma Willis and Vivian Nguyen Awarded Canada Graduate Scholarships-Master’s for 2025-2026

Emma Willis and Vivian Nguyen, both students in the Med-i CREATE program, have been awarded the prestigious Canada Graduate Scholarships-Master’s (CGS M) for the 2025-2026 academic year.

Projects

Integration, federation, and retrieval of large-scale data repositories in Canada

We collaborate with the Canadian Institute of Health Information (CIHI) and the Ontario Health Data Platform (OHDP) to tackle novel challenges in data management and devise evaluation frameworks that center on security, performance and fairness.

Next generation of actionable prescriptive analysis using multi-resolution, multi-modality data

We build computation models of disease from multi-omics data using machine learning, deep learning and evolutionary algorithms, focusing on innovations that address the unique nature of health data and the unavailability and vagueness of gold-standard labels (e.g., pathology labels).

Democratization of AI, software and data for healthcare

We're international leaders in developing and disseminating open source software using low-cost point-of-care imaging. Our positive impact on the global computer–assisted medical interventions community has is constantly expanding. We'll meet new challenges for discovery, refinement of methods and innovative AI-powered solutions using large open source data, hence democratizing access to care and positive outcomes of AI.